Department of Economics and Business Economics

A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory

Research output: Working paperResearch

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  • rp13_24

    Submitted manuscript, 716 KB, PDF document

  • Nima Nonejad, Denmark
We propose a flexible model to describe nonlinearities and long-range dependence in time series dynamics. Our model is an extension of the heterogeneous autoregressive model. Structural breaks occur through mixture distributions in state innovations of linear Gaussian state space models. Monte Carlo simulations evaluate the properties of the estimation procedures. Results show that the proposed model is viable and flexible for purposes of forecasting volatility. Model uncertainty is accounted for by employing Bayesian model averaging. Bayesian model averaging provides very competitive forecasts compared to any single model specification. It provides further improvements when we average over nonlinear specifications.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages24
Publication statusPublished - 19 Aug 2013
SeriesCREATES Research Papers
Number2013-24

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